Background and Purpose
Regulating P2X7 receptor‐mediated activation of NLRP3 inflammasomes could be a therapeutic strategy to treat alcoholic hepatosteatosis. We investigated whether this process was ...modulated by gentiopicroside, the main active secoiridoid glycoside from Gentiana manshurica Kitagawa.
Experimental Approach
In vivo models of acute and chronic alcoholic hepatosteatosis were established by intragastrically administered ethanol or using chronic plus binge ethanol feeding of Lieber‐DeCarli liquid diet to male C57BL/6 mice. In vitro, HepG2 cells were treated with ethanol. RAW 264.7 macrophages and murine bone marrow‐derived macrophages (BMDMs) were stimulated with LPS and ATP.
Key Results
In both the acute and chronic alcohol‐induced mouse hepatosteatosis models, gentiopicroside decreased serum aminotransferases and triglyceride accumulation. Up‐regulated SREBP1, down‐regulated PPARα and phosphorylated acetyl‐CoA carboxylase caused by acute and chronic alcohol feeding were modulated by gentiopicroside, through the elevation of LKB1 and AMPK. Suppression of P2X7 receptor‐NLRP3 activation by gentiopicroside inhibited IL‐1β production. In ethanol‐exposed HepG2 cells, gentiopicroside reduced lipogenesis and promoted lipid oxidation via activation of P2X7 receptor‐NLRP3 inflammasomes. Genetic or pharmacological blockade of P2X7 receptors enhanced AMPK activity and reduced SREBP1 expression in ethanol‐treated HepG2 cells. Gentiopicroside down‐regulated P2X7 receptor‐mediated inflammatory responses in LPS/ATP‐stimulated RAW 264.7 macrophages and BMDMs. IL‐1β from macrophages accelerated lipid accumulation in hepatocytes. Depleting macrophages by clodronate liposomes ameliorated alcoholic hepatosteatosis, and it was further alleviated by gentiopicroside.
Conclusions and Implications
Activation of LKB1/AMPK signalling by gentiopicroside was mediated by the P2X7 receptor‐NLRP3 inflammasome, suggesting the therapeutic value of blocking P2X7 receptors in the treatment of alcoholic hepatosteatosis.
The immunosuppressive microenvironment that is shaped by hepatic metastatic pancreatic ductal adenocarcinoma (PDAC) is essential for tumor cell evasion of immune destruction. Neutrophils are ...important components of the metastatic tumor microenvironment and exhibit heterogeneity. However, the specific phenotypes, functions and regulatory mechanisms of neutrophils in PDAC liver metastases remain unknown. Here, we show that a subset of P2RX1-negative neutrophils accumulate in clinical and murine PDAC liver metastases. RNA sequencing of murine PDAC liver metastasis-infiltrated neutrophils show that P2RX1-deficient neutrophils express increased levels of immunosuppressive molecules, including PD-L1, and have enhanced mitochondrial metabolism. Mechanistically, the transcription factor Nrf2 is upregulated in P2RX1-deficient neutrophils and associated with PD-L1 expression and metabolic reprogramming. An anti-PD-1 neutralizing antibody is sufficient to compromise the immunosuppressive effects of P2RX1-deficient neutrophils on OVA-activated OT1 CD8+ T cells. Therefore, our study uncovers a mechanism by which metastatic PDAC tumors evade antitumor immunity by accumulating a subset of immunosuppressive P2RX1-negative neutrophils.
Renal segmentation is one of the most fundamental and challenging task in computer aided diagnosis systems. In order to overcome the shortcomings of automatic kidney segmentation based on deep ...network for abdominal CT images, a two-stage semantic segmentation of kidney and space-occupying lesion area based on SCNN and ResNet models combined with SIFT-flow transformation is proposed in paper, which is divided into two stages: image retrieval and semantic segmentation. To facilitate the image retrieval, a metric learning-based approach is firstly adopted to construct a deep convolutional neural network structure using SCNN and ResNet network to extract image features and minimize the impact of interference factors on features, so as to obtain the ability to represent the abdominal CT scan image with the same angle under different imaging conditions. And then, SIFT Flow transformation is introduced, which adopts MRF to fuse label information, priori spatial information and smoothing information to establish the dense matching relationship of pixels so that the semantics can be transferred from the known image to the target image so as to obtain the semantic segmentation result of kidney and space-occupying lesion area. In order to validate effectiveness and efficiency of our proposed method, we conduct experiments on self-establish CT dataset, focus on kidney organ and most of which have tumors inside of the kidney, and abnormal deformed shape of kidney. The experimental results qualitatively and quantitatively show that the accuracy of kidney segmentation is greatly improved, and the key information of the proportioned tumor occupying a small area of the image are exhibited a good segmentation results. In addition, our algorithm has also achieved ideal results in the clinical verification, which is suitable for intelligent medicine equipment applications.
The diversity of tree species and the complexity of land use in cities create challenging issues for tree species classification. The combination of deep learning methods and RGB optical images ...obtained by unmanned aerial vehicles (UAVs) provides a new research direction for urban tree species classification. We proposed an RGB optical image dataset with 10 urban tree species, termed TCC10, which is a benchmark for tree canopy classification (TCC). TCC10 dataset contains two types of data: tree canopy images with simple backgrounds and those with complex backgrounds. The objective was to examine the possibility of using deep learning methods (AlexNet, VGG-16, and ResNet-50) for individual tree species classification. The results of convolutional neural networks (CNNs) were compared with those of K-nearest neighbor (KNN) and BP neural network. Our results demonstrated: (1) ResNet-50 achieved an overall accuracy (OA) of 92.6% and a kappa coefficient of 0.91 for tree species classification on TCC10 and outperformed AlexNet and VGG-16. (2) The classification accuracy of KNN and BP neural network was less than 70%, while the accuracy of CNNs was relatively higher. (3) The classification accuracy of tree canopy images with complex backgrounds was lower than that for images with simple backgrounds. For the deciduous tree species in TCC10, the classification accuracy of ResNet-50 was higher in summer than that in autumn. Therefore, the deep learning is effective for urban tree species classification using RGB optical images.
Acetic acid bacteria (AAB) are a group of Gram-negative and strictly aerobic microorganisms widely used in vinegar industry, especially the species belonging to the genera
Acetobacter
and
...Komagataeibacter
. The environments inhabited by AAB during the vinegar fermentation, in particular those natural traditional bioprocesses, are complex and dynamically changed, usually accompanied by diverse microorganisms, bacteriophages, and the increasing acetic acid concentration. For this reason, how AAB survive to such harsh niches has always been an interesting research field. Previous omic analyses (e.g., genomics, proteomics, and transcriptomics) have provided abundant clues for the metabolic pathways and bioprocesses indispensable for the acid stress adaptation of AAB. Nevertheless, it is far from fully understanding what factors regulate these modular mechanisms overtly and covertly upon shifting environments. Bacterial toxin-antitoxin systems (TAS), usually consisting of a pair of genes encoding a stable toxin and an unstable antitoxin that is capable of counteracting the toxin, have been uncovered to have a variety of biological functions. Recent studies focusing on the role of TAS in
Acetobacter pasteurianus
suggest that TAS contribute substantially to the acid stress resistance. In this mini review, we discuss the biological functions of type II TAS in the context of AAB with regard to the acid stress resistance, persister formation and resuscitation, genome stability, and phage immunity.
Key points
•
Type II TAS act as regulators in the acid stress resistance of AAB.
•
Type II TAS are implicated in the formation of acid-tolerant persister cells in AAB.
•
Type II TAS are potential factors responsible for phage immunity and genome stability.
Acetic acid accumulation is a universal limiting factor to the vinegar manufacture because of the toxic effect of acetic acid on the acid producing strain, such as
Acetobacter pasteurianu
s. In this ...study, we aimed to investigate the genome-wide transcriptional response of
A. pasteurianus
Ab3 to high acid stress during vinegar production. By comparing the transcriptional landscape of cells harvested from a long-term cultivation with high acidity (70 ± 3 g/L) to that of low acidity (10 ± 2 g/L), we demonstrated that 1005 genes were differentially expressed. By functional enrichment analysis, we found that the expression of genes related to the two-component systems (TCS) and toxin-antitoxin systems (TAS) was significantly regulated under high acid stress. Cells increased the genome stability to withstand the intracellular toxicity caused by the acetic acid accumulation by repressing the expression of transposases and integrases. Moreover, high acid stress induced the expression of genes involved in the pathways of peptidoglycan, ceramide, and phosphatidylcholine biosynthesis as well as the Tol-Pal and TonB-ExbB systems. In addition, we observed that cells increased and diversified the ATP production to resist high acid stress. Transcriptional upregulation in the pathways of pyrroloquinoline quinone (PQQ) synthesis and thiamine metabolism suggested that cells may increase the production of prosthetic groups to ensure the enzyme activity upon high acid stress. Collectively, the results of this study increase our current understanding of the acetic acid resistance (AAR) mechanisms in
A. pasteurianus
and provide opportunities for strain improvement and scaled-up vinegar production.
Key Points
•
TCS and TAS are responsive to the acid stress and constitute the regulating networks.
•
Adaptive expression changes of cell envelope elements help cell resist acid stress.
•
Cells promote genome stability and diversify ATP production to withstand acid stress.
Elucidation of the acetic acid resistance (AAR) mechanisms is of great significance to the development of industrial microbial species, specifically to the acetic acid bacteria (AAB) in vinegar ...industry. Currently, the role of population heterogeneity in the AAR of AAB is still unclear. In this study, we investigated the persister formation in AAB and the physiological role of HicAB in
Acetobacter pasteurianus
Ab3. We found that AAB were able to produce a high level of persister cells (10
−2
to 10
0
in frequency) in the exponential-phase cultures. Initial addition of acetic acid and ethanol reduced the ratio of persister cells in
A. pasteurianus
by promoting the intracellular ATP level. Further, we demonstrated that HicAB was an important regulator of AAR in
A. pasteurianus
Ab3. Strains lacking
hicAB
showed a decreased survival under acetic acid exposure. Deletion of
hicAB
significantly diminished the acetic acid production, acetification rate, and persister formation in
A. pasteurianus
Ab3, underscoring the correlation between
hicAB
, persister formation, and acid stress resistance. By transcriptomic analysis (RNA-seq), we revealed that HicAB contributed to the survival of
A. pasteurianus
Ab3 under high acid stress by upregulating the expression of genes involved in the acetic acid over-oxidation and transport, 2-methylcitrate cycle, and oxidative phosphorylation. Collectively, the results of this study refresh our current understanding of the AAR mechanisms in
A. pasteurianus
, which may facilitate the development of novel ways for improving its industrial performance and direct the scaled-up vinegar production.
Key points
• AAB strains form persister cells with different frequencies.
• A. pasteurianus are able to form acid-tolerant persister cells.
• HicAB contributes to the AAR and persister formation in A. pasteurianus Ab3.
This paper proposed a novel fusion scheme for muti-modal medical images that utilizes both the features of the multi-scale transformation and deep convolutional neural network. Firstly, the source ...images are decomposed by the Gauss-Laplace filter and Gaussian filter into several sub-images in the first layer of network. Then, HeK-based method is used to initialize the convolution kernel of the rest layers, construct the basic unit, and use the back propagation algorithm to train the basic unit; Train multiple basic units that are sacked with the thought of SAE to get the deep stacked neural network; the proposed network is adopted to decompose the input images to obtain their own high frequency and low frequency images, and combine the our fusion rule to fuse the two high frequency and low frequency images, and put them back to the last layer of the network to get the final fusion images. The performance of our proposed fusion method is evaluated by conducting several experiments on the different medical image datasets. Experimental results demonstrate that our proposed method does not only produce better results by successfully fusing the different images, but also ensures an improvement in the various quantitative parameters as compared to other existing methods. In addition, the speed of our improved CNN method is much faster than that of comparison algorithms which have good fusion quality.
In cells, myriad membrane-interacting proteins generate and maintain curved membrane domains with radii of curvature around or below 50 nm. To understand how such highly curved membranes modulate ...specific protein functions, and vice versa, it is imperative to use small liposomes with precisely defined attributes as model membranes. Here, we report a versatile and scalable sorting technique that uses cholesterol-modified DNA 'nanobricks' to differentiate hetero-sized liposomes by their buoyant densities. This method separates milligrams of liposomes, regardless of their origins and chemical compositions, into six to eight homogeneous populations with mean diameters of 30-130 nm. We show that these uniform, leak-resistant liposomes serve as ideal substrates to study, with an unprecedented resolution, how membrane curvature influences peripheral (ATG3) and integral (SNARE) membrane protein activities. Compared with conventional methods, our sorting technique represents a streamlined process to achieve superior liposome size uniformity, which benefits research in membrane biology and the development of liposomal drug-delivery systems.
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•A three-dimensionally porous graphene (3D-pGR) has been facilely fabricated.•The 3D-pGR has high surface area and large pore volume.•The planar π-configuration of 3D-pGR is ...advantageous for bilirubin adsorption.•The adsorption capacity of 3D-pGR for BSA-bonded bilirubin is extraordinary high.•This material has a negligible hemolysis effect.
The development of bilirubin adsorbents with high adsorption efficiencies towards albumin-bonded bilirubin is still a considerable challenge. In this work, a three-dimensionally porous graphene (3D-pGR) has been fabricated through a simple carbon dioxide (CO2) activation of thermally exfoliated graphite oxide (EGO). Intriguingly, the resultant 3D-pGR material showed hierarchically micro-meso-macroporous structure, high specific surface area of up to 843m2g−1, and large pore volume as high as 2.71cm3g−1. Besides, the large planar π-configuration structure of 3D-pGR made it possible to compete effectively with albumin for bilirubin binding. Taking advantages of these fantastic characteristics, the 3D-pGR was demonstrated to be extraordinarily efficient for bilirubin removal from a bovine serum albumin (BSA)-rich solution. Under optimized conditions, the maximum adsorption capacity of 3D-pGR for BSA-bonded bilirubin was up to 126.1mgg−1, which is not only significantly higher than the adsorption capacities of currently available adsorbents towards albumin-bonded bilirubin, but also superior to those of many reported adsorbents towards free bilirubin. In addition, the hemolysis assay of 3D-pGR indicated that this material had negligible hemolysis effect. Findings from this study may open up important new possibilities for removal of protein-bonded toxins.
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